Triple
T4246054
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Country Grammar |
E95529
|
entity |
| Predicate | worldwideSales |
P22826
|
FINISHED |
| Object | over 10 million copies worldwide |
—
|
LITERAL FINISHED |
How this triple was built (2 steps)
Every LLM step that produced this triple, in pipeline order — named-entity classification, the disambiguation choices (the exact options shown, with the pick highlighted), and the generated description. The batch + timestamp of each is in the Provenance table below.
NER
Named-entity recognition
gpt-5-mini
Instruction
Given a phrase, classify it is english named entity (e.g., persons, organizations, works of art) in Latin script, or not (e.g., literals, dates, URLs, verbose phrases). For disambiguation, the statement where the phrase occurs as object is also given. Please return a JSON object with `phrase` (string, the phrase being analyzed) and `is_ne` (boolean, indicating whether the phrase is a Named Entity).
Input
Phrase: over 10 million copies worldwide | Statement: [Country Grammar, worldwideSales, over 10 million copies worldwide]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: worldwideSales Context triple: [Country Grammar, worldwideSales, over 10 million copies worldwide]
-
A.
salesWorldwide
chosen
Indicates a relationship where an entity’s sales figures or activities are measured, reported, or occur across multiple countries or global markets.
-
B.
soldCopies
Indicates that a certain number of copies of an item were sold by a seller (or in a context) to buyers.
-
C.
usedWorldwide
Indicates that something is utilized or applied across many countries or regions around the world.
-
D.
currencyOfBoxOfficeGrossWorldwide
Indicates the currency in which the worldwide box office gross amount is denominated.
-
E.
boxOfficeGrossUSD
Indicates the total amount of money an entity earned at the box office, expressed in U.S. dollars.
- F. None of above.
Provenance (3 batches)
The batch behind each pipeline step, in order, with when it ran. Timestamps are batch-level — stages were processed in waves, so the object chain (NER → NED1 → NEDg → NED2) reads in order, but predicate / elicitation batches can sit in a different wave.
| Step | Stage | Batch ID | Status | When |
|---|---|---|---|---|
| creating | Elicitation | batch_69b3453d91548190b4d4ef8fe52aa2ac |
completed | March 12, 2026, 10:59 p.m. |
| NER | Named-entity recognition | batch_69b34e8db5bc8190873c5ae3753aaa58 |
completed | March 12, 2026, 11:38 p.m. |
| PD | Predicate disambiguation | batch_69b347f587148190a1830503459939b6 |
completed | March 12, 2026, 11:10 p.m. |
Created at: March 12, 2026, 11:05 p.m.